Patterns Of Engagement Research Articles

Social Engagement is Associated with Location-based Digital Markers on a Dementia Care Unit.

Social Engagement is Associated with Location-based Digital Markers on a Dementia Care Unit.

The relationship between demographics, behavioral and experiential engagement factors, and the use of artistic creative activities to regulate emotions.

There has been increasing interest in the role of artistic creative activities in supporting emotion regulation. However, there is little research about how demographic factors (such as age, gender, ethnicity, personality, and socioeconomic status) or factors relating to creative engagement (including engagement behaviors and subjective experience of engagement) influence our ability to use artistic creative activities to regulate our emotions. We analyzed data from 40,949 adults and used a structural equation modeling approach to model the relationships among demographic factors, factors relating to engagement, and our use of emotion regulation strategies (ERSs) while engaging in artistic creative activities. We found that women make more use of creative activities to regulate their emotions than do men, as do those of lower socioeconomic status. Training in doing an artistic activity, regular engagement, and enjoyment while engaging are all associated with a greater ability to use artistic activities to regulate our emotions. We also identified relationships between demographic and engagement factors and specific types of ERSs, such as avoidance strategies (e.g., distraction, suppression, or detachment from negative or stressful emotions), approach strategies (e.g., acceptance, reappraisal and problem solving), and self-development strategies (e.g., enhanced self-identity, improved self-esteem, and increased agency). Artistic creative activities are increasingly being recognized as effective ways of regulating emotional responses. Overall, this study provides insight into the interrelationship between individual attributes, modifiable patterns of engagement and emotion regulation when engaging in artistic activities

YouTube Text Sentiment Analysis

An innovative approach to YouTube content analytics by combining sentiment analysis of viewer comments with video performance metrics. Our methodology integrates natural language processing techniques and machine learning algorithms to classify comments as positive, negative, neutral, relevant, and irrelevant, while also extracting key insights from video transcripts. By synthesizing video metrics such as views, likes, and engagement with sentiment intelligence, the system delivers comprehensive understanding of audience behavior. The results, visualized through interactive dashboards, empower content creators to refine their strategies for maximum impact. Our implementation achieved 90% accuracy in sentiment classification, demonstrating the effectiveness of our approach for content evaluation and strategic decision-making.Through the fusion of quantitative metrics and qualitative sentiment analysis, our system enables creators to identify content themes that resonate with audiences, recognize patterns in viewer engagement, and optimize content strategy accordingly. The interactive visualization tools facilitate intuitive exploration of complex relationships between sentiment distribution and performance indicators. This holistic analytical framework provides actionable insights that transcend traditional analytics, allowing for more nuanced understanding of audience preferences and behavior. Our approach has significant implications for content optimization and audience development strategies in the growing digital content ecosystem.

Unlocking the power of social media: Exploring how Facebook use attitude influences the political participation of young female adults

ABSTRACT The evolving role of social media in shaping political engagement has drawn significant scholarly attention, with Facebook emerging as a key platform for civic discourse. While prior research has explored the political implications of Facebook use, the influence on young women – a demographic often overlooked in political communication studies – remains underexamined. This study investigates how attitudes toward Facebook use affect political attitudes and participation among young female adults (ages 18–24). Drawing on a survey of 241 university students, the findings reveal that positive attitudes toward Facebook use are significantly associated with higher levels of political self-efficacy and institutional political support. Moreover, political self-efficacy and situational political involvement serve as key mediating mechanisms linking Facebook engagement to political behaviors. These results offer new insights into gendered patterns of digital civic engagement and underscore the relevance of uses and gratifications theory in understanding social media’s democratic potential. The study contributes to theoretical development, methodological refinement, and practical strategies for enhancing political participation among underrepresented groups.

Safeguarding youtube discussions: a framework for detecting anomalous commenter and engagement behaviors

In today’s digital landscape, YouTube’s comment sections play an essential role in shaping public opinion and discussions. However, coordinated groups often exploit these platforms to spread misinformation and distort conversations. This study introduces a method to detect and quantify such anomalous behavior on YouTube channels by analyzing two key components: commenter behaviors and engagement patterns. Focusing on channels concerning news outlets, geopolitics, and the military, we draw from a dataset with 71 channels, 642,952 videos, 12,425,587 commenters, 123,882,200 comments, 139,985,870 subscribers, and 83,396,188,807 views. Our approach leverages key engagement indicators, such as comments, views, and subscriber counts, alongside an analysis of frequent commenter interactions to identify anomalous patterns. We apply unsupervised techniques, including kernel density estimation (KDE) and Gaussian mixture model (GMM), to assign a score reflecting anomalous commenter behavior. To provide a comprehensive measure of this behavior, we combine commenter and engagement scores both at the feature level and at the output level. At the feature level, we employ cosine similarity and principal component analysis (PCA). At the output level, we propose three scoring methods: harmonic mean (HM), weighted average with interaction term (WAIT), and agreement-weighted maximum (AWM). The resulting score, normalized between 0 and 1, indicates the level of anomalous activity on each channel. We validate our results by comparing detected anomalous channels with actual suspended channels from YouTube, confirming the model’s real-world applicability. By offering a quantifiable measure of this activity, our method helps preserve the integrity of YouTube discussions.

Patterns of engagement with professional development among in-service primary music teachers in China and their associations with teaching readiness, school identification, and job satisfaction: A latent profile analysis

Professional development (PD) is widely regarded as essential for enhancing the teaching quality and professional engagement of music educators. In the Chinese context, PD initiatives, including structured teacher training and research engagement, aim to align music education practices with national curriculum reforms and evolving educational demands. However, the diverse patterns of PD engagement among in-service primary music teachers and their associations with teaching readiness, school identification, and job satisfaction remain underexplored. This study investigates these relationships through a latent profile analysis of 375 Chinese primary school music teachers. Five distinct profiles were identified: High-Load Teachers, Research-Oriented Teachers, Training-Oriented Teachers, Balanced Teaching and Training Teachers, and Low-Load Teachers. The results revealed that Training-Oriented and Balanced Teaching and Training Teachers demonstrated the highest levels of teaching readiness, school identification, and job satisfaction, highlighting the effectiveness of practice-oriented training in fostering professional engagement. Conversely, Research-Oriented Teachers exhibited the lowest scores across these dimensions, underscoring the challenges associated with an excessive focus on research, such as inadequate classroom preparation and diminished institutional alignment. These findings emphasize the need for tailored, balanced PD strategies that integrate research and practical training to address the unique needs of music teachers.

Exploring Conceptual Transfer Dynamics in an Online Community of Inquiry

In the context of the growing prevalence of online education, it is imperative to examine the role of group interactions in the development of individual capabilities. This study explores the dynamics of conceptual transfer within an asynchronous online Community of Inquiry (CoI) by employing Social Network Analysis (SNA) with a focus on stochastic investigation for empirical network analysis. The elements of Social Presence (SP), Cognitive Presence (CP), and Threshold Concepts (TCs) are extracted when students interact and reflect on their learning. The analysis of time series data and network evolution is used to discern patterns in student engagement and the emergence of TCs. Bilateral structures were identified, encompassing both the overall communication for the CoI and the dyadic communication for TCs. Knowledge exchange extended to the small-world network of 132 students. Messages that included TCs were infrequent, indicating difficulties in acquisition. Many achievers underwent early transformation. Nodes associated with TCs were not aggregated, but rather dispersed and interlinked across the community. For the creation of deep learning, fostering students’ ability to perceive unfamiliar cognitive paradigms and assimilate information within the subject domain was paramount. The results help to clarify how students in the online learning community can engage in deep and meaningful learning.

A Study on the Paradigm of Biographical Films Based on Intermedia Theory

Biographical films, as an intersection of art, society, and media, hold significant value in both historical representation and contemporary cultural narratives. Media transitions shape the evolution of biographical films by influencing their creation processes, modes of dissemination, and patterns of audience engagement. Using analytical and comparative methods, the study examines how shifts in media influence narrative techniques, protagonist selection, and audience reception. Traditional biographical films often focused on elite figures and innate genius, while modern works emphasize personalized and diverse portrayals, reflecting contemporary media trends. In the digital age, biographical films incorporate interactivity and audience participation, evolving into active cultural memory nodes. These findings highlight the genre’s adaptability, its ability to construct immersive storyworlds, and its engagement with fragmented, decentralized audiences. Biographical films balance historical authenticity with intermedia innovation, redefining the relationship between media, history, and cultural production.

Youth benefit finding and caregiving in a parental illness context: a latent profile analysis

IntroductionThis study used a person-centred approach to identify patterns of engagement in benefit finding (BF) and caregiving among youth who have a parent with a serious illness.MethodsA total of 403 youth completed questionnaires in a cross-sectional study.ResultsLatent profile analyses revealed four profiles. The distribution of caregiving and participants across profiles reflected the caregiving continuum. The ‘low BF & caregiving profile’ had the lowest caregiving and the highest proportion of participants at the low end of the continuum, while the ‘moderate BF & extremely high caregiving profile’ had the highest caregiving and the lowest proportion of participants at the high end. The two mid-continuum profiles reflected mid-to-high proportions of caregiving and participants. Results highlighted a corresponding continuum in BF, where engagement varies in sync with caregiving intensity. Profiles differed on demographics, caregiving context, health-related quality of life (HRQoL), and mental health variables. The two mid-continuum profiles reported high caregiving and moderate-to-high BF and evidenced better HRQoL and mental health than the profile at the highest end of the caregiving continuum, but worse HRQoL and mental health than the profile at the lowest end. Despite high caregiving, these two profiles exhibited moderately high HRQoL and mental health, indicating that BF mitigates the adverse impacts of high caregiving. Results also supported the BF theoretical proposal that caregiving must be sufficiently intense to trigger BF.DiscussionSupport services should reduce youth caregiving responsibilities and encourage youth caregivers to explore the positive aspects of their caregiving role.

Primary and Emergency Care Use: The Roles of Health Literacy, Patient Activation, and Sleep Quality in a Latent Profile Analysis

Background/Objectives: Healthcare utilization is a behavioral phenomenon influenced by psychosocial factors. This study took place in South Tyrol, a culturally diverse autonomous province in northern Italy, and aimed to identify latent profiles of primary healthcare users based on health literacy, patient activation, sleep quality, and service use, and to examine the sociodemographic and health-related predictors of profile membership. Methods: A cross-sectional survey was conducted with a representative adult sample (n = 2090). The participants completed the questionnaire in German or Italian. Latent profiles were identified via model-based clustering using Gaussian mixture modeling and four z-standardized indicators: total primary healthcare contacts (general practice and emergency room visits), HLS-EU-Q16 (health literacy), PAM-10 (patient activation), and B-PSQI (sleep quality). The optimal cluster solution was selected using the Bayesian Information Criterion (BIC). Kruskal–Wallis and chi-square tests were used for between-cluster comparisons of the data. Multinomial logistic regression was used to examine the predictors of cluster membership. Results: Among the 1645 respondents with complete data, a three-cluster solution showed a good model fit (BIC = 19,518; silhouette = 0.130). The identified profiles included ‘Balanced Self-Regulators’ (72.8%), ‘Struggling Navigators’ (25.8%), and ‘Hyper-Engaged Users’ (1.4%). Sleep quality could be used to differentiate between different levels of service use (p < 0.001), while low health literacy and patient activation were key features of the high-utilization groups. Poor sleep and inadequate health literacy were associated with increased healthcare contact. Conclusions: The latent profiling revealed distinct patterns in health care engagement. Behavioral segmentation can inform more tailored and culturally sensitive public health interventions in diverse settings such as South Tyrol.

Early Detection and Prevention of Malicious User Behaviour on Twitter Using Deep Learning Techniques

Malicious user behavior on Twitter, such as spam, harassment, and disinformation, can degrade the platform's integrity and user experience. Traditional detection techniques often struggle to detect emerging threats in real time. This paper presents a deep learning-based approach for the early detection and prevention of malicious user behavior on Twitter. By analyzing user interactions, tweet content, and engagement patterns, the system predicts and identifies potentially harmful users before they escalate their behavior. The model leverages Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks, incorporating features such as linguistic characteristics, temporal patterns, and user metadata. Experimental results show that the proposed system achieves a 92.3% accuracy, outperforming traditional methods in both detection rate and prevention capability. This system can assist in early intervention, significantly reducing the harmful impact of malicious users on the platform.

Designing gamified branching scenarios on a technological platform to enhance clinical reasoning in dental education

Abstract Simulation and gamification offer valuable pedagogical approaches, providing safe environments for dental students to practice complex professional skills. Developing clinical reasoning is crucial as students perform irreversible procedures early in their training. Traditional methods may offer limited opportunities to experience decision consequences without risking patient harm. Simulation based learning in a branching scenario (BrSc) format, that incorporates gamification and productive failure (Kapur, 2008), bridges the gap between preclinical theory and clinical practice, addressing the need for engaging, relevant learning experiences (ASE Strategy). This project aligns with the University's ASE Strategy, 'A curriculum defined by quality and relevance' through innovative, inquiry-based learning and authentic assessment, and 'Environments and systems that enable innovation' by leveraging digital technologies. This presentation details the design, implementation, and preliminary evaluation of a gamified BrSc developed to support clinical reasoning and understanding decision consequences for second-year dental and oral health students managing atypical dental pain. Informed by a validated serious gaming model (Argueta-Muñoz, 2023) and based on an authentic patient case, the BrSc was designed as an interactive narrative where student choices determine progression through multiple pathways. Key gamified features included 17 strategically placed 'learning points' representing common clinical errors, branching pathways with unique information and a dashboard for tracking progress. The design supported productive failure, allowing students to navigate suboptimal pathways discovering learning points which provided tailored feedback prompting them to revisit decisions. A Design-Based Research (DBR) approach guided the project, emphasising iterative design and evaluation in a real-world classroom setting. A survey platform (Qualtrics) was selected for development due to its branching logic capabilities, built-in reporting for learning analytics, and low technical barrier to entry. Evaluation data included learning analytics automatically captured by the platform (tracking pathway choices, attempts, time, learning points unlocked), direct classroom observations of student engagement and interaction patterns (individual vs. collaborative), and qualitative feedback from students. Preliminary results from implementation with 149 students (775 attempts) indicate the gamified BrSc fostered high engagement. The gamified 'learning point' tracking appeared effective; classroom observations showed students, particularly when working collaboratively after an initial individual attempt, actively discussed pathways and were motivated to explore different options, including incorrect paths, to 'unlock' all points. Learning analytics provided valuable insights for educators, visualising common decision pathways via Sankey diagrams and identifying specific points of difficulty, informing potential teaching interventions (ASE Strategy: Use of analytics to support the student experience). Student feedback directly informed iterative improvements, such as adding skip functionality for previously completed sections. The tool facilitated peer learning and discussion, contributing to 'A community in which This work demonstrates how survey platforms can be effectively repurposed to create sophisticated, gamified BrSc for complex skill development. It offers insights into specific gamification design choices and their observed effects on student engagement and learning behaviour. It highlights the utility of learning analytics for informing educational practice and curriculum refinement, supporting evidence-based teaching (ASE Strategy: Valuing excellence in education). A brief demonstration of the branching scenario's gamified elements, discussion of the design decisions and challenges, and posing a reflective question: "How might the principles of gamified feedback and pathway exploration be adapted using technologies within your own teaching context to enhance student learning through simulation?" References Argueta-Muñoz FD, Olvera-Cortés HE, Durán-Cárdenas C, Hernández-Gutiérrez L, Gutierrez-Barreto SE. Instructional design and its usability for branching model as an educational strategy. Cureus [Internet]. 2023 May 18 [cited 2023 Sep 5];15(5). Available from: https://research.ebsco.com/linkprocessor/plink?id=18f651fd-54f2-316d-8038-e6d44d4b1e4c Kapur M. Productive failure. Cogn Instr [Internet]. 2008 Jul 1 [cited 2023 Sep 4];26(3):379–425. Available from: https://research.ebsco.com/linkprocessor/plink?id=80f6be87-d06d-3d8b-9aa7-f03a246ed424 White, M., Dal Santo, K., Copley, J., Mustchin, C., and Jones, B. (2024). Designing branching scenarios to support clinical reasoning in dental education. In Cochrane, T., Narayan, V., Bone, E., Deneen, C., Saligari, M., Tregloan, K., Vanderburg, R. (Eds.), Navigating the Terrain: Emerging frontiers in learning spaces, pedagogies, and technologies. Proceedings ASCILITE 2024. Melbourne (pp. 415-419). https://doi.org/10.14742/apubs.2024.1150

A Survey of the United Kink-dom: Investigating Five Paraphilic Interest Groups and Their Demographic and Psychological Correlates

ABSTRACT We explored demographic, psychological, and behavioral characteristics of five paraphilic interest groups in the UK: BDSM, pet play, age play/ABDL, furries, and balloon fetishists – chosen for their prevalence, power dynamics, and varied activities. Through an anonymous survey (N = 470), we assessed role identities, engagement patterns, and relational dynamics. Groups were more likely to have non-heterosexual, non-monogamous, and non-cisgender identities, with high levels of co-occurrence across paraphilic interests. Participants were predominantly cisgender men, though over 25% identified as non-cisgender. Men were more likely to take on dominant roles, women submissive roles, and nonbinary people switch roles. There were differences in Dark Triad traits based on role identity. A minority of participants did not pair their interests with sex, especially pet players and furries. Bimodal distributions in the centrality of paraphilic interests to sexual identity underscore implications for sub-group classification and add to discourse of paraphilias as a dimension of sexual orientation. Relationship satisfaction correlated with shared paraphilic interests. Some associations were found between age play and pedophilic fantasies and behaviors and pet play/furries and zoophilic fantasies and behaviors, but this was only for a small minority. This work expands on existing literature by contextualizing findings within broader societal and relational frameworks and addressing stigmatized stereotypes. Recommendations include longitudinal and cross-cultural studies to explore the evolution of paraphilic interests and their intersection with psychosocial variables.

A COMPARATIVE ANALYSIS OF ADVERTISINGSTRATEGIESINEMERGING MARKETS: CONSUMER ENGAGEMENT, TRUST, ANDEFFECTIVENESS

AIM: By analyzing customer trust, engagement, and purchase patterns, this studyaimstoevaluate the efficacy of traditional and digital advertising strategies in emerging economies. This study intends to close the research gap by examining customer preferences inlight ofcontemporary digital marketing trends and technology breakthroughs, even if previousresearch has examined advertising methods. Material And Methods: This study analyzedWeb of Science and Google Scholar literature and gathered primary data from100participants split into conventional (TV, radio, print, billboards) and digital (social media, search engines, apps) advertising groups using a self-made Google Forms questionnaire. Tables, charts, and graphs were used to visualize the data, which was analyzed usingMSExcel and SPSS IBM Version 27 using the Independent T-Test, One-Way ANOVA, andChi-Square test. Results and Discussion: With an Independent T-Test p-value of 0.051 (<0.05), the research showed a substantial correlation between advertising forms and consumerpurchase decisions, suggesting that ads have a major influence on consumer behavior. TheOne-Way ANOVA findings showed that, with an F-value of 0.704 and a p-value of 0.051(<0.05), storytelling-based ads generate more engagement than simple promotional content. While conventional advertising is still essential for establishing trust, particularly withgroups who have less digital adoption, the results indicate that digital advertising, with its interactivefeatures and personalized targeting, improves consumer engagement. In order to optimizeefficacy in emerging countries, the study also emphasizes the significance of a hybridadvertising strategy that combines traditional and digital tactics. Conclusion: Accordingtothe report, younger consumers like digital advertising since it is more interactive, but conventional advertising is still essential for building a brand reputation. To increase trust andengagement, businesses should take a balanced approach. Future studies should look at cross-platform tactics, data protection, and AI-driven marketing to improve campaign efficacy.

Assessing The Relationship Among Academic Engagement, Well-being, And Mental Health: Featuring University Students Seeking Support at a Counseling Facility

Abstract Given the high prevalence of psychological distress and mental health conditions within higher education contexts, identifying potential factors fostering university students’ well-being may be pertinent. Academic engagement (AE) appears to play a key role in supporting mental health and buffering psychological issues. This study addressed the association between AE, well-being, and mental health among university students, by focusing on a specific vulnerable sub-population: those who seek support at a university counseling facility. The main objectives were to identify distinct patterns of AE, to examine differences among these patterns, and to explore how they are associated with various psychological well-being and mental health outcomes. Data were collected from 650 students (M = 23.9; SD = 3.2) attending the counseling facility. Standardized questionnaires were used to measure AE, anxiety, depression, emotion regulation, and psychological distress. Three distinct patterns of academic engagement were identified through a clustering process: Low AE pattern, Moderate AE pattern, and High AE pattern. Multivariate statistical analyses were conducted to examine the associations between these patterns and various well-being and mental health outcomes. Results indicated significant associations between higher levels of academic engagement and improved psychological well-being. Conversely, lower engagement was associated with more severe psychological symptoms and distress. These findings suggest that students’ AE should be considered as an integral component of counseling interventions. By highlighting the connection between AE and mental health, this study provides insights for designing effective strategies tailored on students’ needs, enhancing mental health and favoring a supportive educational environment.

Exploring gender differences in empathy development among medical students: a qualitative analysis of reflections on juvenile correctional school visits

ABSTRACT Empathy development is a critical component of medical education, shaping future physicians’ ability to provide compassionate, patient-centered care. This study investigates the reflections of male and female medical students on their experiences at a juvenile correctional school, focusing on how gender shapes their interpretations, emotional engagement, and learning outcomes. Using a qualitative analysis of reflective journals collected from 28 participants, the study employed thematic analysis to identify gender-based patterns in emotional engagement, interpretive framing, and learning outcomes. Reflexivity measures and rigorous coding processes were implemented to ensure credibility and minimize bias in data interpretation. Male students frequently adopted a practical form of empathy, characterized by task-oriented interactions and a sense of competitive camaraderie. In contrast, female students exhibited relational empathy, emphasizing emotional connections and nurturing behaviors. These findings underscore the value of integrating gender-sensitive empathy training into medical education, encouraging the development of both relational and practical approaches. By incorporating tailored reflection exercises and interactive strategies, medical education programs can better equip students to engage compassionately with diverse patient populations. This approach enriches the learning experience and fosters a more holistic understanding of patient care, ultimately leading to improved healthcare outcomes.

Stuttering Representation on X: A Detailed Analysis of Content, Sentiment, and Influences.

Social media shapes public perceptions of various topics, including health conditions and communication challenges, such as stuttering. This study analyzed the stuttering-related posts on X (formerly Twitter), a platform chosen for its unique features, including real-time interaction, concise messaging, and public accessibility. X's hashtag system also enables efficient tracking of trends and aggregating relevant posts, making it ideal for thematic and sentiment analysis. This study examined X to explore how stuttering is represented and perceived in top stuttering-related posts. It focused on these posts' themes, sentiments, and engagement patterns, as well as their influence on perceptions of stuttering on the platform. In this exploratory study, data from 153 highly engaged posts containing the hashtag "#stuttering" were analyzed using sentiment analysis, thematic analysis, and network analysis. Posts were selected based on engagement scores calculated from the number of likes, comments, and reposts. The sentiment analysis revealed that 69.93% of posts conveyed positive sentiments, with the majority of these posted by self-identified stuttering advocates, while 6.54% reflected negative sentiments and 23.53% were neutral. Five key themes emerged from the data: (a) celebrating stuttering success, (b) enhancing awareness and education about stuttering, (c) navigating challenges through support, (d) addressing misconceptions and reducing stigma, and (e) systematic advocacy and policy reform. Network analysis reflected the critical role of health care professionals and advocacy organizations in shaping public perceptions. This study highlighted both the supportive and stigmatizing aspects of stuttering representation on X. While prominent figures and organizations drive positive engagement, targeted efforts are still needed to address negative stereotypes. These findings provide insights for future public health communication and advocacy strategies in the stuttering community.

Generative AI-driven personalization of the Community of Inquiry model: enhancing individualized learning experiences in digital classrooms

PurposeThis paper explores the integration of generative artificial intelligence (GenAI) into the Community of Inquiry (CoI) framework, focusing on how GenAI can dynamically personalize online learning environments. The study aims to examine how GenAI can enhance social, cognitive and teaching presence, thus meeting the diverse needs of individual learners and improving engagement in digital classrooms.Design/methodology/approachThe paper employs a conceptual approach, building on existing literature about the CoI framework and GenAI. It proposes a theoretical model that illustrates how GenAI can personalize social, cognitive and teaching presence in real-time, using engagement patterns, performance data and feedback mechanisms to adapt learning pathways for individual students.FindingsThe study finds that GenAI can significantly enhance personalized learning by dynamically adjusting the CoI framework’s elements. GenAI-driven interactions improve student engagement through personalized prompts and adaptive content delivery, while AI-generated feedback provides timely and individualized support, fostering a more responsive and student-centered learning experience.Practical implicationsFor educators, the integration of GenAI into the CoI framework offers scalable solutions for personalized instruction and feedback. Institutions can leverage AI-driven insights to create more adaptive, learner-centered environments that improve learning outcomes, satisfaction and engagement, especially in large-scale online courses.Social implicationsThe paper highlights the potential for AI-driven education to bridge gaps in personalized learning, promoting equity and inclusivity. However, it also addresses ethical concerns such as data privacy, algorithmic bias and the digital divide, urging careful implementation to ensure that AI enhances rather than undermines educational fairness.Originality/valueThis paper provides a novel perspective on the intersection of GenAI and the CoI framework, proposing a unique conceptual model for AI-enhanced online education. It offers valuable insights for educators, researchers and institutions aiming to create more personalized, effective and inclusive digital learning environments.

Public spheres or echo chambers? Nonprofit E-advocacy and civic engagement on harm reduction policy in the U.S.

Public spheres or echo chambers? Nonprofit E-advocacy and civic engagement on harm reduction policy in the U.S.

Feasibility and usability evaluation of a gamified fatigue management mobile application for persons with multiple sclerosis in everyday life.

Feasibility and usability evaluation of a gamified fatigue management mobile application for persons with multiple sclerosis in everyday life.